The Plant Associated Microbe Gene Ontology has added more than 700 words to an ongoing three-year Gene Ontology term-development initiative, and presented them as part of eight papers in a special supplement to BMC Microbiology.
The PAMGO Consortium developed the ontology with the goal of addressing a lack of vocabulary in the area of microbe-host interactions, and of helping researchers better mine full genome sequences and allowing them to do cross-genome analysis.
PAMGO is a multi-institutional effort formed in 2004 and includes the Virginia Bioinformatics Institute at the Virginia Polytechnic Institute and State University; the Institute for Genome Sciences at the University of Maryland School of Medicine; Cornell University; North Carolina State University; the University of Wisconsin, Madison; Wells College in Aurora, NY; and the European Bioinformatics Institute in the UK.
By developing new GO terms the scientists want to improve data mining results from genome sequence and high-throughput microarray and proteomic analyses that shed light on microbes and hosts.
"The community-driven Gene Ontology resource is a big step forward in allowing researchers to make comparisons across microbial species of the many processes involved in microbe-host environment interactions," says Brett Tyler, PAMGO project leader, co-author of five of the eight papers, and Virginia Bioinformatics Institute researcher.
He adds that he hopes the scientific community will contribute to this controlled vocabulary based on its own research findings.
"Extending the GO to include terms specific to pathogen function is a watershed step for infectious disease researchers," says Fiona McCarthy, a researcher at the College of Veterinary Medicine at Mississippi State University. She was not part of the PAMGO effort but is part of the Gene Ontology Consortium, which works on ontology development. "Now we can use existing GO tools to functionally model host-pathogen interactions," she adds.
— Vivien Marx
Oxford Gene Technology is partnering with Optra Systems. The collaboration is geared toward visualizing and analyzing data from high-resolution scanners and is now in the testing phase following initial software development.
Genedata and Syngenta are collaborating on biomarker discovery on LC-MS and GC-MS metabolomic raw data processing and analysis. Syngenta has added Genedata's Refiner MS to integrate mass spec data in biomarker discovery projects.
The nonprofit research organization National Center for Genome Resources will be partnering with Floragenex, a genetic technology company. Floragenex will bring its proprietary genomic discovery and application tools to the sequencing and bioinformatics capabilities of NCGR.
Amount raised by Genelogics For ongoing expansion plans.
BiologicalNetworks: Integrated Environment for Systems Biology
Grantee: Michael Baitaluk, San Diego Supercomputer Center
Began: Sep. 15, 2008; Ends: Jun. 30, 2012
This grant will assist efforts aimed at extending Biological-Networks, a biomedical analysis environment developed by the Keck Graduate Institute and the San Diego Supercomputer Center, into a modular, extensible software platform where a wider variety of complex biological data can be efficiently managed and integrated.
Statistical Algorithms for Valid Inferences in Genomic Data
Grantee: George Casella, University of Florida
Began: Sep. 1, 2008; Ends: Aug. 31, 2011
Casella will use this grant to develop data methods applicable to SNP association genetics and clustering methods for time-course data based on Bayesian hierarchical models and Metropolis-Hastings search algorithm with the specific goal of developing a new classifier that associates clusters, or gene patterns, with clinical outcomes.